Speaker: Matei Zaharia

Assistant Professor of Computer Science @Stanford and Chief Technologist @Databricks

Matei Zaharia is an assistant professor of computer science at Stanford and Chief Technologist of Databricks, the data and ML infrastructure company based around Apache Spark. He started the Spark project while he was a PhD student at UC Berkeley. He has also contributed to other open source big data systems including Apache Mesos and Apache Hadoop. At Stanford, Matei does research on systems for machine learning as part of the DAWN project.

Find Matei Zaharia at

Keynote : Panel: Building a Data Science Capability (Live Recording of The InfoQ Podcast)

Tracks

  • Deep Learning Applications & Practices

    Deep learning lessons using tooling such as Tensorflow & PyTorch, across domains like large-scale cloud-native apps and fintech, and tacking concerns around interpretability of ML models.

  • Predictive Data Pipelines & Architectures

    Best practices for building real-world data pipelines doing interesting things like predictions, recommender systems, fraud prevention, ranking systems, and more.

  • ML in Action

    Applied track demonstrating how to train, score, and handle common machine learning use cases, including heavy concentration in the space of security and fraud

  • Real-world Data Engineering

    Showcasing DataEng tech and highlighting the strengths of each in real-world applications.